Gender Recognition by Voice Using Machine Learning

被引:0
|
作者
Bhatia, Rohit [1 ]
Singh, Nagendra Pratap [1 ]
机构
[1] Natl Inst Technol Hamirpur, Hamirpur, India
来源
ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2021 | 2022年 / 1534卷
关键词
Acoustic features; MFCC; LPC; KNN; SVM; Uniform distribution; Normalization; Gaussian distribution;
D O I
10.1007/978-3-030-96040-7_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently, gender recognition has become an important area of research. Gender recognition can be used in various fields like for security purposes, speaker identification and speaker recognition. Various techniques has been used to identify the gender of person like using facial analysis, voice identification, machine learning, deep learning, using features like LPC and MFCC. This paper deals with identifying the gender using Acoustic properties of voice using Machine learning and how the accuracy vary when dataset goes through different transformation. It shows that we achieve maximum accuracy when uniform transformation is applied on dataset in case of KNN and SVM both.
引用
收藏
页码:307 / 318
页数:12
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